It is widely accepted that a good approach to building handwriting recognition devices such as Tablet PCs or Pocket PCs is to employ a machine learning model such as a neural network. Achieving good “walkup accuracy” for the large variety of writing styles requires the collection of handwriting samples from many individuals with a large variety handwriting styles. The samples in turn are used to train a handwriting recognizer. Such a recognizer will perform well for popular styles, but less well for less common or unusual handwriting styles.